code: def __init__(self, channels, kernel_size=3, stride=1, padding=1):
      super().__init__()
  
      self.sequence = nn.Sequential(
          nn.Conv2d(
              channels, channels, kernel_size, stride, padding=padding
          ),
          _channel_norm_2d(channels, affine=True),
          nn.ReLU(),
          nn.Conv2d(
              channels, channels, kernel_size, stride, padding=padding
          ),
          _channel_norm_2d(channels, affine=True),
      )
  
file_path: NeuralCompression/neuralcompression/models/_hific_encoder_decoder.py
imports: from typing import List
  import torch
  import torch.nn
  from torch import Tensor
  from neuralcompression.layers import ChannelNorm2D
label_desc: Use image node_id 1 to create a new _ResidualBlock object from inherited base classes: torch.nn with example: obj = _ResidualBlock(channels, kernel_size, stride, padding)